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BACKGROUND: In Madagascar, the districts of Antsirabe II, Faratsiho and Antsiranana I have relatively low malaria incidence rates and have been selected by the National Malaria Control Programme for pilot elimination strategies. The districts have residual transmission despite increasing coverage and quality of malaria services. This study sought to identify priority subpopulations at highest risk for malaria and collect information on intervention preferences and methods that will inform subnational tailoring of malaria service delivery. METHODS: This mixed methods study employed (i) a quantitative malaria risk factor assessment in Antsirabe II and Faratsiho comprising a test-negative frequency matched case-control study and a qualitative risk factor assessment in Antsiranana I; and (ii) a qualitative formative assessment in all three districts. For the case-control study, a mixed effects logistic regression was used with age, sex and district included as fixed effects and health facility included as a random effect. The qualitative risk factor assessment used semi-structured interview guides and key informant interviews. For the qualitative formative assessment in the three districts, a summary report was generated following semi-structured interviews and focus group discussions with high-risk populations (HRPs) and stakeholders. RESULTS: In Antsirabe II and Faratsiho districts, rice agriculture workers, outdoor/manual workers, particularly miners, and those with jobs that required travel or overnight stays, especially itinerant vendors, had higher odds of malaria infection compared to other (non-rice) agricultural workers. In Antsiranana I, respondents identified non-rice farmers, mobile vendors, and students as HRPs. Risk factors among these groups included overnight stays and travel patterns combined with a lack of malaria prevention tools. HRPs reported treatment cost and distance to the health facility as barriers to care and expressed interest in presumptive treatment and involvement of gatekeepers or people who have influence over intervention access or participation. CONCLUSIONS: The study results illustrate the value of in-depth assessments of risk behaviours, access to services and prevention tools, surveillance and prevention strategies, and the involvement of gatekeepers in shaping subnational tailoring to reach previously unreached populations and address residual transmission in elimination settings.

Fungal sinusitis encompasses a wide range of diseases, including both invasive and noninvasive, acute, and chronic forms. The incidence of invasive sinusitis is on the rise, primarily affecting immunocompromised individuals and diabetics. This case report highlights a patient who developed invasive fungal sinusitis despite no other apparent cause of immunosuppression. Imaging studies suggested the diagnosis, confirmed by presence of Aspergillus flavus on mycological culture.

Abstract The evaluation of white matter lesions (WMLs) showing the central vein sign (CVS) and paramagnetic rim lesions (PRLs) has been suggested to enhance the diagnostic work‐up of adult multiple sclerosis (MS). We aimed to evaluate the fulfillment of different CVS criteria and the added value of PRLs in 22 pediatric MS patients. Eleven patients (50%) fulfilled the 40%‐rule threshold. Nineteen (86%) patients had ≥3 CVS+ WMLs or ≥1 PRL, whereas 17 (77%) had ≥6 CVS+ WMLs or ≥1 PRL. A simplified CVS‐based approach, with the combined evaluation of ≥1 PRL in patients with ≥6 CVS+ WMLs, may improve MS diagnosis in pediatric patients.

Abstract Introduction Abdominal surgical emergencies have a high mortality rate. Effective management primarily relies on the early identification of patients at high risk of postoperative complications. The objective of our study was to determine the prognostic factors associated with poor outcomes from abdominal surgical emergencies in Senegal and to establish a predictive score for mortality for preoperative risk evaluation (NDAR (New Death Assessment Risk) score). Methodology This was a retrospective national cross-sectional study conducted over one year in 14 regions of Senegal. Adult patients (aged > 15 years) who presented with a traumatic or non-traumatic abdominal surgical emergency were included. The studied variables included clinical and paraclinical data. The variable of interest was death within 30 days of the surgery. Logistic regression was used to identify the factors independently associated with mortality. Risk factors identified after logistic regression analysis were weighted using odds ratio (OR) values rounded to the nearest whole number. The predictive capacity of the score was evaluated by analyzing the ROC (Receiver Operating Characteristic) curve based on the area under the curve (AUC). Results A total of 1114 patient records were included, with a mortality rate of 4.4%. Diagnoses were observed in patients included appendicitis in 39.8% of cases (n = 444), followed by peritonitis in 22.3% (n = 249), intestinal obstruction in 18.5% (n = 205), strangulated hernias in 10.5% (n = 117), and abdominal trauma in 6.1%. Logistic regression, established the following scores: age > 40 years (score 2), ASA status grade 2 or higher (score 1), presence of a positive QSIRS score (score 2), diagnosis of peritonitis (score 2), diagnosis of intestinal obstruction (score 1), and the presence of intestinal necrosis (score 3). The score is positive if the total is strictly greater than 5, indicating a 17.7% risk of mortality. This score had a high predictive capacity with an AUC of 0.7397. Conclusion This study enabled the establishment of a score that allows for the early identification of at-risk patients, even in constrained resource settings, facilitating appropriate perioperative management and timely surgical intervention to reduce the risk of complications. This approach, focused on early recognition of high-risk patients, is crucial for improving clinical outcomes in abdominal surgical emergencies.

The authors present a Web application they designed in the R programming language as an experiential learning tool for teaching production theory. The app simulates production decisions where a manager is tasked to find the optimal mixture of inputs through experimentation. Users of the application are instructed to use calculations and intuitions from production theory to improve profitability quickly. The underlying parameters and starting points are randomized to allow for additional practice. Variations of the exercise correspond to cost-minimization and profit-maximization problems with and without market power in the output market. Also, the app provides dynamic, interactive visualizations in 3D in order to assist in a better understanding of standard production theory graphs. The app is located at https://bit.ly/387HsHL.

Imperforate hymen is a rare malformation (1/ 1000 female births). It is diagnosed most often during puberty. Early diagnosis of hematocolpos and evacuation is necessary to avoid any consequences. We report a rare case of an imperforate hymen complicated with acute urinary retention, hydronephrosis and renal failure in a 14-year-old girl to emphasize the possible misdiagnosis and its possible consequences. This is the first case we encounter in our unit. Keywords: Hymen, imperforate, hymenectomy , hydronephrosis, renal failure.

In plant roots, arbuscular mycorrhizal fungi (AMF) are the most prevalent microsymbionts, and thereby provide many key ecosystem services to natural and agricultural ecosystems. Despite AMF’s significance for the environment and the economy, little is known about the mycorrhizal inoculum potential and diversity of AMF associated with orphan African cereal crops, specially fonio millet (Digitaria exilis stapf.) under field conditions. We hypothesized that the type of fonio millet agroecosystem influences the AMF density and distribution in soils. We therefore, assessed the inoculum potential, density and diversity of AMF spores and soil enzyme activities in five fonio millet agroecosystems belonging to three climatic zones (Sudanian, Sudano-Sahelian and Sudano-Guinean). By combining AMF spore identification from field-collected soils and trap culture, 20 species belonging to 8 genera (Acaulospora, Ambispora, Dendiscutata, Gigaspora, Glomus, Racocetra, Sclerocystis and Scutellospora) were identified. Glomus was the most represented genus with 8 species, followed by Gigaspora (5 species) and Acaulospora (2 species); the remaining genera were each represented by one species. Except for Ambispora which was not found in the Sudanian area, all genera occurred in the three climatic zones. The abundance and diversity of AMF species and FDA-hydrolytic and phosphatase activities varied between fonio millet agroecosystems as well as between climatic zones. Soil pH and soil texture were the variables that best explained the density and distribution of AMF spores. Our results contribute to paving the way towards the development of microbial engineering approaches for agronomic improvement of fonio millet.

The Hodgkin variant Richter syndrome (HvRS) is an infrequent complication occurring in 1% of lymphocytic lymphoma/chronic lymphocytic leukemia patients. We report a case of HvRS diagnosed in Sub-Saharan Africa. A 63-year-old patient was consulted for the investigation of an abdominal mass that had been evolving for 5 years prior to admission. His history revealed night sweats, 13% weight loss in 3 months and persistent pruritis. Examination revealed bilateral cervical axillary and inguinal macroadenopathies, painless abdominal distension, pruritic lesions and WHO 2 PS. The blood count showed anemia at 9.5 g/dL. Histology revealed a lymphomatous proliferation of diffuse architecture, nodular in places, with Hodgkin and Sternberg cells associated with small lymphocytes, histiocytes and eosinophilic polymorphs. Immunohistochemistry showed CD20, PAX5, BCL2, CD5, CD23 and MYC positivity; Ki67 at 10% and cyclin D1, BCL6 and CD10 negativity; CD30 positivity on Hodgkin and Sternberg cells that remained CD20 negative; difficulty interpreting CD15; EBV positivity (EBERs); and CD3 and CD5 positivity on reactive T cells. CD138 and kappa and lambda light chains were non-contributory. The extension work-up classified the patient as Ann Arbor stage III B with a Hasenclever score of 3/7. This case illustrates the difficulties in diagnosing HvRS in our countries, where the number of haematopathologists is insufficient and the technical facilities are limited.

Abstract Important policy questions during infections disease outbreaks include: i) How effective are particular interventions?; ii) When can resource-intensive interventions be removed? We used mathematical modelling to address these questions during the 2017 Ebola outbreak in Likati Health Zone, Democratic Republic of the Congo (DRC). Eight cases occurred before 15 May 2017, when the Ebola Response Team (ERT; co-ordinated by the World Health Organisation and DRC Ministry of Health) was deployed to reduce transmission. We used a branching process model to estimate that, pre-ERT arrival, the reproduction number was $$R=1.49$$ R = 1.49 (95% credible interval $$({{{{\mathrm{0.67,2.81}}}}})$$ ( 0.67, 2.81 ) ). The risk of further cases occurring without the ERT was estimated to be 0.97 (97%). However, no cases materialised, suggesting that the ERT’s measures were effective. We also estimated the risk of withdrawing the ERT in real-time. By the actual ERT withdrawal date (2 July 2017), the risk of future cases without the ERT was only 0.01, indicating that the ERT withdrawal decision was safe. We evaluated the sensitivity of our results to the estimated $$R$$ R value and considered different criteria for determining the ERT withdrawal date. This research provides an extensible modelling framework that can be used to guide decisions about when to relax interventions during future outbreaks.

Monitoring subnational healthcare quality is important for identifying and addressing geographic inequities. Yet, health facility surveys are rarely powered to support the generation of estimates at more local levels. With this study, we propose an analytical approach for estimating both temporal and subnational patterns of healthcare quality indicators from health facility survey data. This method uses random effects to account for differences between survey instruments; space-time processes to leverage correlations in space and time; and covariates to incorporate auxiliary information. We applied this method for three countries in which at least four health facility surveys had been conducted since 1999 - Kenya, Senegal, and Tanzania - and estimated measures of sick-child care quality per WHO Service Availability and Readiness Assessment (SARA) guidelines at programmatic subnational level, between 1999 and 2020. Model performance metrics indicated good out-of-sample predictive validity, illustrating the potential utility of geospatial statistical models for health facility data. This method offers a way to jointly estimate indicators of healthcare quality over space and time, which could then provide insights to decision-makers and health service program managers.

Résumé : Administrateur colonial en Oubangui-Chari, l’une des quatre colonies relevant du Gouvernement Général de l’Afrique Équatoriale Française (A.E.F.), René Maran est surtout connu pour son roman Batouala qui a obtenu le Prix Goncourt en 1921. Pourtant il est l’auteur d’une importante production littéraire composée de nouvelles, de contes et de romans. Elle est intitulée le ‘’Cycle de la brousse africaine’’. Parmi les romans, Le livre de la brousse sera l’objet de notre étude. Usant de l’esthétique naturaliste, Maran y décrit, sans faire de jugement, le cadre géographique du pays banda et ses composantes : hommes et animaux. Mots-clés : africain, française, esthétique, narration, pionnier, roman.

Introduction: Sub-Saharan Africa struggles continuously with insufficient resources and inadequate infrastructure that hinder the establishment of a safer blood supply despite improvements in transfusion safety over recent decades. This study aimed to evaluate the impact of the chemiluminescence technique in combination with immunoenzymatic and immunochromatographic tests for viral marker screening of hepatitis B (HBV), hepatitis C (HCV) and human immunodeficiency virus (HIV) in donated blood in a country of sub-Saharan Africa. Method: This study was conducted in a population of 113,406 blood donors at the National Centre of Blood Transfusion in Senegal. The data were obtained from the ‘INLOG’ software and donor registers. Statistical analyses used Excel 2010 and Epi Info v6. Screening for HBsAg viral markers, anti-HCV Ab, HIV p24 Ag, anti-HIV1 and anti-HIV2 antibodies were first carried out using the chemiluminescence technique. Blood donations screened positive for HBV or HCV were retested in a second chemiluminescence equipment. HIV-positive donations and their controls were subjected to solid phase immunochromatographic and indirect enzyme immunoassay techniques. Results: The prevalence among donors of HBV was 8.39 %, 0.56 % for HCV and 0.18 % for HIV. Of the donors tested positive for HIV in screenings and in doubled-controls, only 61.54 % were confirmed by the alternative tests; 34.02 % were negative and 4.44 % discordant between the three techniques. Conclusion: This study shows the importance of introducing the chemiluminescence technique in association with serological screening of transfusion-transmitted viruses to improve blood supply safety in low-income countries.

IntroductionGenetic improvement in rice increased yield potential and improved varieties for farmers over the last decades. However, the demand for rice is growing while its cultivation faces challenges posed by climate change. To address these challenges, rice breeding programs need to adopt efficient breeding strategies to provide a steady increase in the rate of genetic gain for major traits. The International Rice Research Institute (IRRI) breeding program has evolved over time to implement faster and more efficient breeding techniques such as rapid generation advance (RGA) and genomic selection (GS). Simulation experiments support data-driven optimization of the breeding program toward the desired rate of genetic gain for key traits. MethodsThis study used stochastic simulations to compare breeding schemes with different cycle times. The objective was to assess the impact of different genomic selection strategies on medium- and long-term genetic gain. Four genomic selection schemes were simulated, representing the past approaches (5 years recycling), current schemes (3 years recycling), and two options for the future schemes (both with 2 years recycling). ResultsThe 2-Year within-cohort prediction scheme showed a significant increase in genetic gain in the medium-term horizon. Specifically, it resulted in a 22%, 24%, and 27% increase over the current scheme in the zero, intermediate, and high genotype-by-environment interaction (GEI) contexts, respectively. On the other hand, the 2-Year scheme based on between-cohort prediction was more efficient in the long term, but only in the absence of GEI. Consistent with our expectations, the shortest breeding schemes showed an increase in genetic gain and faster depletion of genetic variance compared to the current scheme. DiscussionThese results suggest that higher rates of genetic gain are achievable in the breeding program by further reducing the cycle time and adjusting the target population of environments. However, more attention is needed regarding the crossing strategy to use genetic variance optimally.

Objectives Our research adopts computational techniques to analyze disease outbreaks weekly over a large geographic area while maintaining local-level analysis by incorporating relevant high-spatial resolution cultural and environmental datasets. The abundance of data about disease outbreaks gives scientists an excellent opportunity to uncover patterns in disease spread and make future predictions. However, data over a sizeable geographic area quickly outpace human cognition. Our study area covers a significant portion of the African continent (about 17,885,000 km 2 ). The data size makes computational analysis vital to assist human decision-makers. Methods We first applied global and local spatial autocorrelation for malaria, cholera, meningitis, and yellow fever case counts. We then used machine learning to predict the weekly presence of these diseases in the second-level administrative district. Lastly, we used machine learning feature importance methods on the variables that affect spread. Results Our spatial autocorrelation results show that geographic nearness is critical but varies in effect and space. Moreover, we identified many interesting hot and cold spots and spatial outliers. The machine learning model infers a binary class of cases or none with the best F 1 score of 0.96 for malaria. Machine learning feature importance uncovered critical cultural and environmental factors affecting outbreaks and variations between diseases. Conclusions Our study shows that data analytics and machine learning are vital to understanding and monitoring disease outbreaks locally across vast areas. The speed at which these methods produce insights can be critical during epidemics and emergencies.